{"id":"W4305057907","doi":"10.1371/journal.pcbi.1010533","title":"Calibrating spatiotemporal models of microbial communities to microscopy data: A review","year":2022,"lang":"en","type":"review","venue":"PLoS Computational Biology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Calibration; Data mining; Machine learning; Data science; Model selection; Artificial intelligence; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002910624,0.002137468,0.002373858,0.002469012,0.0003080924,0.00149473,0.002841165,0.002082391,0.002168405],"category_scores_gemma":[0.006644693,0.0009254691,0.001661955,0.003103644,0.0008385761,0.002757114,0.001170252,0.001736897,0.002135479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007996964,"about_ca_system_score_gemma":0.001860455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002594627,"about_ca_topic_score_gemma":0.001867233,"domain_scores_codex":[0.999351,0.0001439548,0.00008603046,0.0001738236,0.0002169025,0.00002832288],"domain_scores_gemma":[0.9954385,0.003419378,0.0002897779,0.0001904388,0.0005778491,0.00008397713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004929726,0.00008698129,0.0008242479,0.02580359,0.0003668182,0.0001479676,0.00008808392,0.02284563,0.002661616,0.02222593,0.01819271,0.906707],"study_design_scores_gemma":[0.00003795935,0.0003044338,0.002534818,0.0130864,0.0008883351,0.001159414,0.000133114,0.02464886,0.005364849,0.04186879,0.9096777,0.0002952002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000505848,0.9725935,0.02447007,0.0005178517,0.0003263907,0.00002467478,0.0001867528,0.0001466874,0.001228215],"genre_scores_gemma":[0.003653996,0.9836907,0.0113287,0.0002203006,0.00031734,0.00004884458,0.0002698657,0.00005435284,0.0004158908],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002910624,"threshold_uncertainty_score":0.01539308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1978918696816784,"score_gpt":0.3692615249241805,"score_spread":0.1713696552425021,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}